Nomogram for predicting survival after lymphatic metastasis in esophageal cancer: A SEER analysis

Lymphatic metastasis (LM) is a significant mechanism for the spread of esophageal cancer (EC) and predicts the poor prognosis of EC patients. This research aimed to assess the survival of patients with LM from EC by developing a nomogram. In this retrospective study, EC patients with LM from 2004 to 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were divided by year of diagnosis into a training cohort and a validation cohort. Univariate and multivariate Cox regression analyses were employed to determine the prognostic factors of LM, and a nomogram was constructed. The discrimination and calibration of the nomogram were compared by the C-index, area under the curve value, and calibration plots. The survival time difference was compared using Kaplan–Meier curves. A total of 11,695 patients with EC were included in this analysis. LM occurred in 56.5% (n = 6614) of EC patients. In the post-propensity score matching (PSM) cohort, patients with LM had significantly lower median overall survival (OS) than those without LM. Multivariate Cox regression was used to identify the eleven independent prognostic factors. The C-index was 0.709 in both the training and test sets, revealing the good predictive performance of the nomogram. Based on the results of calibration plots and the receiver operating characteristic (ROC) curve, we demonstrate the great performance of the prognostic model. The survival time of EC patients with LM was remarkably lower than that of EC patients without LM. The nomogram model established in this study can precisely predict the survival of EC patients with LM.


Introduction
As the most common thoracic malignancy after lung cancer, esophageal cancer (EC) has very high morbidity and mortality. According to Global Cancer Statistics 2020, EC accounted for 3.1% (n = 604,100) of new cases and 5.5% (n = 544,076) of new deaths. [1] As 2 pathological types of EC, adenocarcinoma (AC) and squamous cell carcinoma (SCC) have an uneven global distribution. SCC incidence in Southeast and Central Asia accounts for 79% of the global SCC incidence, while AC in Oceania, North America, Northern Europe, and Western Europe accounts for 46% of the global EAC incidence. [2] Different subtypes of EC have different incidences in different parts of the esophagus. AC is more common in the lower esophagus, while SCC is more common in the upper esophagus. [3] The incidence of esophageal AC has been on the rise in many Western countries in recent years. [4,5] EC spreads rapidly once it develops. Lymphatic metastasis (LM) is one of the most common methods of EC metastasis, and its LM areas include mediastinal lymph nodes, cervical lymph nodes, and abdominal lymph nodes. The esophagus has a unique network of capillary lymphatic vessels, making the lymphatic drainage system extremely complex. [6] Because the lymphatic vessels of the esophagus are located in the submucosa, LM is common in patients with EC, and approximately 52% of patients with EC have LM. [7] Kenshi Kuge et al [8] showed that there WY, YY, an MF contributed equally to this work.

Supported by Natural Science Foundation of Gansu Province (21JR1RA118) and Gansu Provincial Youth Science and Technology Fund (21JR1RA107, 18JR3RA305).
The authors have no conflicts of interest to disclose.
The datasets generated during and/or analyzed during the current study are publicly available. Medicine is a direct esophageal drainage system in the thoracic duct. Lymph spread plays an important role in the prognosis of EC patients. [9] Lymph node status can effectively predict 5-year survival and recurrence of EC. [10] Endoscopic ultrasonography, compute tomography, and positron emission tomography are common methods for diagnosing LM in EC. [9] EC has a higher incidence of LM than other gastrointestinal cancers. [11,12] Wen-Hu Hsu et al [13] found that the number and proportion of lymphatic metastases are independent prognostic elements for EC patients. However, there is no nomogram model for forecasting the survival time of EC patients with LM. Therefore, we constructed a prognostic nomogram model to forecast 1-year, 3-year, and 5-year survival after LM in EC using data from the Surveillance, Epidemiology, and End Results Database (SEER) database between 2004 and 2015.
This study attempts to explore the factors influencing the prognosis of patients with EC and thus guide clinicians' prognostic decisions and investigate the relationship between lymph node metastasis and prognosis in patients with EC. Establishing such a prognostic model may lead to earlier clinical interventions and benefits for EC patients, and the visualization of categories in the nomogram may help clinicians make more accurate judgments and treatments to improve postoperative survival time.

Patient selection
We extracted 11,695 patients with EC discovered between 2004 and 2015 from the SEER database, the largest cancer database in the United States. Included patients with EC must meet all following criteria: first malignant primary indicator and patients aged 19 to 85 with tumor size <600 mm. The exclusion criteria were as follows: incomplete follow-up date, incomplete clinicopathological information, and patients diagnosed by autopsy. Finally, this study included 11,695 patients diagnosed with EC, of whom 6614 developed lymphatic metastases. We . We extracted race, N stage, primary tumor site, sex, grade, radiotherapy, histological type, T stage, chemotherapy, distant metastasis information, surgery, tumor size, age, and follow-up information from the SEER database. We assessed patient survival using overall survival (OS), which is the process from diagnosis to loss to follow-up or all-cause death. The best cutoff values for continuous variables, including tumor size and age, were determined by X-tile v3.6.1 (Yale University). [14] This study applies AJCC TNM 6th edition staging. The SEER database is an open, deidentified database, so we do not require institutional review board approval.

Statistical analysis
We transformed continuous variables into categorical variables using X-tile software and compared differences in categorical variables using the chi-square or Fisher exact test. To exclude the effect of other variables on the prognosis of EC patients with or without LM, 1:1 propensity score matching (PSM) was performed in SPSS v26.0 (SPSS Inc.). Finally, 3697 patients with LM were matched with 3697 patients without LM. In the training cohort, we included factors with P < .05 in multivariate Cox regression from univariate Cox regression to identify independent prognostic factors. According to the results of multivariate Cox regression, a nomogram was established for predicting the prognosis of EC patients with LM. We also verified its validity by receiver operating characteristic (ROC) curve, C-index, calibration plots, and Kaplan-Meier curve analyses.

Survival analysis
We matched a total of 3697 patients with LM with 3697 patients without LM by SPSS V26.0. The median survival in the post-PSM cohort was 14 months (interquartile range 6-45 months). Patient characteristics in the pre-and post-PSM cohorts are shown in Table 1. In the post-PSM cohort, 84.6% (n = 6262) of patients died during follow-up. The median OS was 13.0 (95% CI: 12.5-13.5) months and 22.0 (95% CI: 20.5-23.5) months for patients with EC with and without LM, respectively, in the pre-PSM cohort (Fig. 1A). The median OS was 13.0 (95% CI: 12.3-13.7) months and 17.0 (95% CI: 15.8-18.2) months for patients with EC with and without LM, respectively, in the post-PSM cohort (Fig. 1B).  Table 2. Using SPSS software, we included variables with P < .05 in univariate Cox regression into multivariate Cox regression and finally determined that variables including sex, M stage, surgery, histological type, race, grade, tumor size, T stage, radiotherapy, marital status, and chemotherapy were independent prognostic factors for LM of EC. More details are provided in Table 3.

Construction and verification of the nomogram
According to the results of multivariate Cox regression, a nomogram was built that could accurately predict the prognosis of EC after LM was constructed using R software v4.1.3. The C-index values are highly consistent, both 0.709 (95% CI: 0.701-0.717; 0.695-0.723), indicating that the model has excellent stability in the training set and test set. ROC analysis showed that the www.md-journal.com Table 1 Demographic characteristics before and after PSM. We used the x-tile v3.6.1 (Yale University) to determine the optimal cutoffs for tumor size and age. PSM = propensity score matching.

Discussion
EC is a malignant tumor with poor prognosis and certain mortality in the chest. Symptoms such as esophageal obstruction appear late and usually reach the locally advanced stage or even the metastatic stage at the time of diagnosis. [15] The prognosis for EC remains poor because it often spreads through its unique lymphatic system. Lymphatic status is an important observation indicator that affects patient prognosis in EC. [16] Previous studies have found that approximately 52% of EC patients had LM. [7] In our study, 56.5% (n = 6614) of patients had LM, and the median survival time with LM was remarkably lower than that without LM (P < .001). To exclude the influence of other variables, we performed 1:1 PSM. Despite some limitations, such as the inability to analyze and balance all variables, the confounding bias in observational studies can be reduced by PSM. [17] In the post-PSM cohort, although the median survival time with LM was obviously lower, it was still remarkably higher than that of patients with LM (P < .001). Therefore, it is critical to determine the prognosis of EC patients with LM. Therefore, we conducted this study and constructed a nomogram. Furthermore, the calibration plots and ROC curves illustrated that the nomogram has considerable predictive power. This model will more easily guide clinical practice and enhance the comprehension of prognostic factors.
There have been several studies on the distant metastasis of EC. Shizhao Cheng et al [18] found that bone metastasis, lung metastasis, and T stage were prognostic factors for brain metastasis of EC. Jin Zhang et al [19] found that T stage, sex, marital status, brain metastases, and liver metastases were prognostic factors for bone metastases of EC. In our study, the prognostic factors for patients with LM from EC included sex, grade, race, surgery, T stage, chemotherapy, M stage, radiotherapy, tumor size, histological type, and marital status. Chemotherapy and surgery are the most important factors affecting the prognosis of patients with lymph-positive EC, and chemotherapy and surgery can significantly improve the survival of EC patients. Therefore, clinicians should try to consider chemotherapy and surgery for patients with lymph node metastasis.
Compared with TNM staging, the nomogram is a simpler and more visual tool for estimating the risk based on patient characteristics and is widely used in oncology and medical prognosis. [20] According to the results of multivariate Cox regression, We used the x-tile v3.6.1 (Yale University) to determine the optimal cutoffs for tumor size and age. www.md-journal.com we constructed a nomogram model for predicting the survival of patients with EC LM. It performs well on both the training and validation cohorts. As shown in Figure 4, EC patients with lymph node metastases who did not receive chemotherapy and surgery had significantly lower survival, so surgery and chemotherapy should be considered first for patients with resectable EC. In addition, age, T stage, race, M stage, grade, histological type, radiotherapy, tumor size, and marital status all affect the survival of EC patients with LM. Previous studies have found that marital status affects how long patients live. Some studies have found that marital status and distant metastasis affect patient survival. [21,22]   This study established a prognostic model that can be used to evaluate patients with EC after lymph node metastasis. The visualization feature of the nomogram is helpful for clinicians to make better judgments and target treatment. To verify the stability and effectiveness of the model, we divided all included data into a training set and a validation set according to the year of diagnosis, and the model showed great predictive capacity in both the training cohort and the test cohort.
This retrospective study inevitably has limitations. First, although the SEER database is the largest clinical database in the United States, it contains information on morbidity, mortality, and morbidity for approximately 30% of the U.S. population. However, some aspects of the information are incomplete, such as surgical methods, chemotherapy regimens, dose, radiation dose, and genetic information, which limits our further analysis. Second, there may be errors in the identification of patients with  LM. LM can be confirmed by biopsy in only a minority of cases. When judging LM by CT or positron emission tomography-CT, it is difficult to avoid false positives and negatives. Third, the nomogram constructed in this study was not validated by an external validation cohort.

Conclusion
The survival time of EC patients with LM was remarkably lower than that of EC patients without LM. The nomogram model established in this study can precisely predict the survival of EC patients with LM.